Staff Platform Engineer - Fully Remote, AI-Driven Dev Platform

Jobgether

Ireland

Remote

EUR 120,000 - 160,000

Full time

5 hours ago
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Benefits offered by this job

Fully remote
Competitive salary
Distributed team support
Technical ownership
AI-enabled workflows
Work across Europe and Americas

Job summary

Jobgether is seeking a Staff Platform Engineer based in Ireland to shape our infrastructure and developer experience. You will lead high-impact initiatives focused on continuous delivery, cloud infrastructure, automation, and productivity across distributed teams.

You will drive architectural decisions, own observability and operational tooling, and foster an ownership culture that accelerates AI‑powered engineering workflows while improving reliability and scalability.

Qualifications

  • Extensive experience at Staff Engineer level or equivalent, leading cross-functional initiatives.
  • Ability to influence architecture and engineering standards across teams.
  • Proven track record building scalable cloud infrastructure and developer platforms.

Responsibilities

  • Lead platform engineering initiatives, starting with CI/CD and deployment automation.
  • Improve developer productivity with reliable CI, optimized merge workflows, and local dev environments.
  • Own cloud infra, pipelines, observability, and tooling for a scalable org.
  • Build self-service tooling to reduce friction for engineers and AI-driven workflows.
  • Mentor peers, promote ownership, and drive reliability practices across teams.

Skills

Staff Engineer
Leadership
CI/CD
Cloud infrastructure
Dev experience
AI workflows
Observability
Incident management
Mentoring
Automation

Tools

AWS ECS/Fargate
Terraform/Terragrunt
Datadog

Job description

Jobgether is seeking a Staff Platform Engineer based in Ireland to shape our infrastructure and developer experience. You will lead high-impact initiatives focused on continuous delivery, cloud infrastructure, automation, and productivity across distributed teams.

You will drive architectural decisions, own observability and operational tooling, and foster an ownership culture that accelerates AI‑powered engineering workflows while improving reliability and scalability.

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